Simple Calculated Member Running for Forever - MDX - ssas

I am facing very strange issue with MDX (SSAS 2014), on which simplest calculated member is taking forever to execute. Could someone please help me to understand why i am facing this issue. If i not use calculated member everything works fast and result comes in seconds. When i remove Producer attribute, query performances well.
Below is the complete query.
WITH
MEMBER Measures.AsOfDate AS ("[Policy Effective Date].[Year-Month].[Date].&[2018-01-04T00:00:00]")
MEMBER Measures.YTDPremium AS AGGREGATE (YTD(STRTOMEMBER(Measures.AsOfDate)), [Measures].[Written Premium])
SELECT NON EMPTY
{
Measures.YTDPremium
} ON COLUMNS, NON EMPTY
{
(
[Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
)
} ON ROWS
FROM [Premium]

Try understand what the following part does in your query
NON EMPTY { ( [Program].[Program Name].[Program Name]
,[Insuring Company].[Insuring Company Name].[Insuring Company Name]
,[Line Of Business].[Line Of Business].[Line Of Business]
,[Producer].[Producer Name].[Producer Name]
) } ON ROWS
In the above MDX you are telling the server to take a cross product of all values of "Programs", "Line Of Business" and "Producer Name". So lets say you have 4 values of programs , 3 values of line of business and 2 values of producer name. The total combinations are 4*3*2=24
Now the "Non empty" removes any combinations that are not present in your dataset. This is done by removing all rows that have "Null" value in column value.
Your measure is returning value irrespective if that combination exists or not. You can modify your Calculatedmeasure to return value only in the case if the combination is valid. This can be achived by checking an actual measure for that combination
Edit: based the below example is based on the comment
In the below example i am trying to get the internet sales amount categories and components
select
{ [Measures].[Internet Sales Amount] }
on columns,
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
Now add "Non empty" to the query and observe the results.
Results
Now lets add calculted measure that returns "hello". Notice how the non empty clause is ineffective.
Now modify the code make the calculated measure check other measures for null
with member measures.t as
case when [Measures].[Internet Sales Amount] = null then null else "hello" end
select
{ [Measures].[Internet Sales Amount] ,measures.t }
on columns,
non empty
(
[Product].[Category].[Category],
[Customer].[Country].[Country]
)
on rows
from [Adventure Works]
Result
The bottom line: Because of cross product your result is so huge that SSAS is having hard time handling it.

Related

MDX - transpose rows to columns

I'm trying to display details from two rows into one using MDX. If I execute the MDX below, it returns 2 rows, one containing the 998 Key and one containing the 999 Key
SELECT NON EMPTY {
[Measures].[FactTableCount] } ON COLUMNS,
NON EMPTY { ([DimXXXX].[XXXXKey].[XXXXKey].ALLMEMBERS
* ([DimAAAA].[AAAAKey].[AAAAKey],{[DimBBBB].[Key].&[998],[DimBBBB].[Key].&[999]},[DimCCCC].[CCCCKey].[CCCCKey])
) } ON ROWS
FROM ( SELECT ( { [DimXXXX].[XXXXKey].&[MyValue] } ) ON COLUMNS
FROM [FactTable])
It returns something like this
(columns [DimXXXX].[XXXXKey], [DimAAAA].[AAAAKey], [DimBBBB].[Key], [DimCCCC].[CCCCKey], [Measures].[FactTableCount])
MyValue, MyAAAAKey1, 998, MyCCCCKey1, 1
MyValue, MyAAAAKey2, 999, MyCCCCKey2, 1
However I want to return one row like this
`(columns [DimXXXX].[Key], [DimAAAA].[AAAAKey], [DimAAAA].[AAAAKey], [DimBBBB].[Key], [DimBBBB].[Key], [DimCCCC].[CCCCKey], [DimCCCC].[CCCCKey], [Measures].[FactTableCount])
MyValue, MyAAAAKey1, MyAAAAKey2, 998, 999, MyCCCCKey1, MyCCCCKey2, 1
Among other things (such as using SETs, putting the 998/999 logic after the ROWS/COLUMNS, etc) I've tried
SELECT NON EMPTY {
[Measures].[FactTableCount] } ON COLUMNS,
NON EMPTY { ([DimXXXX].[XXXXKey].[XXXXKey].ALLMEMBERS
* ([DimAAAA].[AAAAKey].[Key],[DimBBBB].[Key].&[998],[DimCCCC].[CCCCKey].[CCCCKey])
* ([DimAAAA].[AAAAKey].[Key],[DimBBBB].[Key].&[999],[DimCCCC].[CCCCKey].[CCCCKey])
) } ON ROWS
FROM ( SELECT ( { [DimXXXX].[XXXXKey].&[MyValue] } ) ON COLUMNS
FROM [FactTable])
...however because the AAAAKey hierarchy is repeated I receive the error message "The AAAAKey hierarchy is used more than once in the Crossjoin function"
Is there a way to do do this ?
Based on your comment below I have a sample.Let me know if it works.
I think I can see what you're saying however the measures are one
thing, but the dimension values are another - say Record1:MyValue,
MyAAAAKey1, 998, MyCCCCKey1, 2 and Record2: MyValue, MyAAAAKey2, 999,
MyCCCCKey2, 5 - I would like to output MyValue, MyAAAAKey1,
MyAAAAKey2, 998, 999, MyCCCCKey1, MyCCCCKey2, 2, 5
So in the query below I am trying to simulate your problem.
select
{[Measures].[Internet Sales Amount]}
on columns,
non empty
([Customer].[City].[City],{[Product].[Category].&[1],[Product].[Category].&[3]},[Product].[Subcategory].[Subcategory])
on rows
from [Adventure Works]
Result
Now onw way is to take the changing values to columns, "{[Product].[Category].&1,[Product].[Category].&2}" in my case and "{[DimBBBB].[Key].&[998],[DimBBBB].[Key].&[999]}" in your case
select
{
({[Product].[Category].&[1],[Product].[Category].&[3]},[Measures].[Internet Sales Amount]),
([Product].[Category].defaultmember,[Measures].[Internet Order Quantity])
}
on columns,
non empty
([Customer].[City].[City],[Product].[Subcategory].[Subcategory])
on rows
from [Adventure Works]
Result:
Note how the values are only repeated for the relevent column. This does add an extra column but you rows are now half the orignal count.
Edit: to handle the requirement based on the comment
1st row of the grid would be Ballard, Bikes, Mountain Bikes, Road
Bikes. The 2nd: Ballard, Clothing, Caps, Gloves. The 3rd: Barstow,
Bikes, Road Bikes, null. I want to merge/list the actual dimension
values
So to achieve above we have two options. But in either case some manipulation on UI would be required.
1)First option
with member
measures.t
as (nonempty(existing([Customer].[City].currentmember,[Product].[Category].currentmember,[Product].[Subcategory].[Subcategory].members),[Measures].[Internet Sales Amount])).item(0).item(2).name
member measures.t1
as (nonempty(existing([Customer].[City].currentmember,[Product].[Category].currentmember,[Product].[Subcategory].[Subcategory].members),[Measures].[Internet Sales Amount])).item(1).item(2).name
select
{measures.t,measures.t1}
on columns,
nonempty(([Customer].[City].[City],{[Product].[Category].&[1],[Product].[Category].&[3]}),[Measures].[Internet Sales Amount])
on rows
from [Adventure Works]
2)The second option,
with member
measures.t1
as
[Customer].[City].currentmember.name
member measures.t2
as
[Product].[Category].currentmember.name
member measures.t3
as (nonempty(existing([Customer].[City].currentmember,[Product].[Category].currentmember,[Product].[Subcategory].[Subcategory].members),[Measures].[Internet Sales Amount])).item(0).item(2).name
member measures.t4
as (nonempty(existing([Customer].[City].currentmember,[Product].[Category].currentmember,[Product].[Subcategory].[Subcategory].members),[Measures].[Internet Sales Amount])).item(1).item(2).name
select
{measures.t1,measures.t2,measures.t3,measures.t4}
on columns,
nonempty(([Customer].[City].[City],{[Product].[Category].&[1],[Product].[Category].&[3]}),[Measures].[Internet Sales Amount])
on rows
from [Adventure Works]

Show items with no data on rows | SSAS , MDX

Working on a task that required to bring all a dimension’s data to the Pivot Table(Excel Sheet) even if they are not related to the fact.
first I was able to do it by using the option “PivotTable Options” -> “Display” -> “Show items with no data on rows” from Excel. The problem here is that using this option is going to affect the other dimensions and the requirement is to only this work for the Student dimension only and the user doesn’t like to keep changing the option back every time. then I found this solution using SCOPE, below, but just like above I could not find an away to just have the scope ignore the logic if any other dimension added so the data does not get duplicated.
SCOPE ([Program].[Program Hierarchy].MEMBERS, [Measures].[Number of Students]);
THIS = IIF(ISEMPTY([Measures].[Number of Students]), 0, ([Measures].[Number of Students]));
END SCOPE;
So is there something that I can add the SCOPE above to just work in the program dimension and get ignore/ skip and work as normal if any other dimension added to the pivot table?
Any suggestion will be appreciated.
Lets suppose that for Dimension1 ,attribute1, and the attribute "Value 1", you had nothing in Fact, so this is removed from the result, now you forced Excel to display it by selecting the option. When you add another dimension's attribute lets say Dimension2.Attribute1, since "Value 1" had nothing in Fact, therefore Cube will not understand which value of of Dimension2.Attribute1 is to be displayed in front of Dimension1.Attribute1, therefore it will display all its values. So if we have 3 values in Dimension2, attribute 1 then "Value 1" will be repeated three times. Now with Excel you cannot solve the issue, however it might just be possible to write an MDX query that works.
Edit: Query Added.
The below sample query is based on AdventureWorks, the first sample shows that the result has some nulls, if i un-comment the "non-empty" all null values will vanish, go ahead try it.
select [Measures].[Internet Sales Amount] on columns,
--non empty
[Product].[Subcategory].[Subcategory]
on rows
from
[Adventure Works]
Result without non empty
Now lets add another dimension to the query. Notice that the null value for the first row(Bib-shorts) is now repeated for all values of the second dimension, Since cube has no way to determine which value to display.
select [Measures].[Internet Sales Amount] on columns,
--non empty
([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year])
on rows
from
[Adventure Works]
Result
Now the above result shows the issue you are facing. What we now need to do is whenever there is a null value we dont need the individual members of the second dimension, rather a place holder to satisfy the tuple, will work.
In the query below I have two tuples
1) for the not null data-points. Here we display the actual member of the second dimension.
2) for the null data-points, here we use ".defaultmember" which basically means that the second dimension will behave as it was never selected. Have a close look at the second dimension it says "All Period"
select [Measures].[Internet Sales Amount] on columns,
--non empty
{filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].[Calendar Quarter of Year]),[Measures].[Internet Sales Amount]>0),
filter(([Product].[Subcategory].[Subcategory],[Date].[Calendar Quarter of Year].defaultmember),[Measures].[Internet Sales Amount]=null)
}
on rows
from
[Adventure Works]
Result:

Non-empty previous value - MDX

I am using Performance Point Dashboard Designer 2013 and SharePoint Server 2013 for building dashboards. I am using SSAS2012 for Cube.
I have a scenario similar to the one illustrated by figure below. I am required to find Previous Non-Empty value for purpose of finding Trends.
Measure: [Quota]
Dimension: [Date].[Calendar Date].[Date]
The script ([Measures].[Quota], [Date].[Calendar Date].PrevMember) gives you a previous date. Lets say for date 27-Jan-13 whose Quota value is 87, it returns 26-Jan-13 which has null value. I want it to return 21-Jan-13 that has some Quota value. And for date 21-Jan-13, I want to return 15-Jan-13.
I wonder if this is possible.
Thanks,
Merin
After long searches and hits & trials and so on, I think I invented a solution of my own for myself.
Following is the script for my Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
Explanation
The number 15 means it will look for non-empty measures up to 15 siblings.
Now we know up to how many siblings to traverse back, in this case 15.
Lets find 15 previous siblings (both empty and non-empty) excluding current member.
(LastPeriods(15, [Date].[Calendar Date].PrevMember)
Since it will yield both empty and non-empty members, lets filter out empty members in terms of measure [Quota]. If we don't specify measure here, it will use default measure whatever it is and we may not get desired result.
Nonempty(LastPeriods(15, [Date].[Calendar Date].PrevMember),[Quota])
We may have several members in the output. And we will choose the last one.
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
)
So far, the script above gives previous non-empty member. Now we want to implement this member for our measure [Quota].
Hence we get the script below ready to create a Calculated Member.
(
[Quota],
Tail
(
Nonempty
( LastPeriods(15, [Date].[Calendar Date].PrevMember)
,[Quota]
)
).Item(0)
)
You can use recursion to define this.
The following query delivers something similar for the Adventure Works cube:
WITH member [Measures].[Prev non empty] AS
IIf(IsEmpty(([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Prev non empty]),
([Date].[Calendar].CurrentMember.PrevMember, [Measures].[Internet Sales Amount])
), format_String = '$#,##0.00'
SELECT {[Measures].[Internet Sales Amount], [Measures].[Prev non empty]}
ON COLUMNS,
non empty
Descendants([Date].[Calendar].[Month].&[2007]&[12], [Date].[Calendar].[Date])
ON ROWS
FROM [Adventure Works]
WHERE [Customer].[Customer].&[12650]
You would have to replace the name of the date hierarchy, as well as the measure name from Internet Sales Amount to Quota in the recursive definition of the measure Prev non empty.

Getting a count of users each day in Mondrian MDX

I'm trying to write a query to give me the total number of users for each customer per day.
Here is what I have so far, which for each customer/day combination is giving the total number of user dimension entries without splitting them up by customer/day.
WITH MEMBER [Measures].[MyUserCount]
AS COUNT(Descendants([User].CurrentMember, [User].[User Name]), INCLUDEEMPTY)
SELECT
NON EMPTY CrossJoin([Date].[Date].Members, [Customer].[Customer Name].Members) ON ROWS,
{[Measures].[MyUserCount]} on COLUMNS
FROM
[Users]
The problem with your calculated member is that [User].CurrentMember is set to the All member for every row tuple, and thus the count is the total. What you need is a way for the [Customer].CurrentMember and [Date].CurrentMember to effectively filter the [User] dimension.
You need to use a measure that makes sense, i.e. that will have a non-empty value for meaningful joins of the dimension members that you're interested in.
To find this out, you could start by running a query like this:
SELECT
NON EMPTY CrossJoin(
[User].[User Name].Members,
[Measures].[Some measuse]
) ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Project]
You would have selected Some measure adequately. The results of that query will be a lot of empty cells, but in a given row, the columns that do have a value correspond to the Users that are related to a given Customer x Date tuple (on the row). You want to count those columns for every row. COUNT and FILTER are what you need, then the query with the calculated member will be
WITH MEMBER [Measures].[User count] AS
COUNT(
FILTER(
[User].[User Name].Members,
NOT ISEMPTY([Measures].[Some measure])
)
)
SELECT
NON EMPTY {[Measures].[User count]} ON COLUMNS,
NON EMPTY CrossJoin(
[Date].[Date].Members,
[Customer].[Customer Name].Members
) ON ROWS
FROM [Users]
I am assuming a fair bit here, but with some experimentation you should be able to work it out.

Can I reformulate this MDX query to use sets instead of an "And"?

with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer]),
Iif(
(IsEmpty(([Item].[ItemNumber].&[011074], [Measures].[Sale Amount]))
And IsEmpty(([Item].[ItemNumber].&[011069], [Measures].[Sale Amount]))
)
Or IsEmpty([Measures].[Sale Amount]),
0 , 1
)
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;
The object is to show all the items purchased by customers who also bought either of the two dispensers (011069 and 011074).
I based the calculated member on a query I found to do basket analysis. I feel like there should be a way to write it with the set {[Item].[ItemNumber].&[011074], [Item].[ItemNumber].&[011069]} instead of the two IsEmpty tests. Everything I've tried ended up having every Customer in the result.
My environment is SQL Server Analysis Services 2005.
Yes I can! It just required a slightly different approach to the calculated member:
with member [Measures].[BoughtDispenser] as
Sum(Descendants([Customer].[Customer].CurrentMember, [Customer].[Customer])
* {[Item].[ItemNumber].&[011069], [Item].[ItemNumber].&[011074]},
[Measures].[Quantity Shipped]
)
select
{[Measures].[Sale Amount]} on columns,
non empty filter([Customer].[Customer].children, [Measures].[BoughtDispenser])
* {[Item].[ItemNumber].members}
on rows
from [Sales]
where [EnteredDate].[Quarter].&[2010-01-01T00:00:00]
;